title: A Bayesian adaptive Phase I-II clinical trial for evaluating efficacy and toxicity with delayed outcomes.
abstract: BACKGROUND
  In traditional Phase-I oncology trials, the safety of a new chemotherapeutic agent is tested in a dose escalation study to identify the maximum tolerated dose, which is defined as the highest dose with acceptable toxicity. An alternate approach is to jointly model toxicity and efficacy and allow dose finding to be directed by a prespecified trade-off between efficacy and toxicity. With this goal in mind, several designs have been proposed to jointly model toxicity and efficacy in a Phase I-II dose escalation study. A factor limiting the use of these designs is that toxicity and efficacy must be observed in a timely manner.
  
  
  OBJECTIVE
  One approach to overcoming this problem is to model toxicity and efficacy as time-to-event outcomes. This would allow new subjects to be enrolled before full information is available for previous subjects while incorporating partial information when adaptively assigning new subjects to a dose level.
  
  
  METHODS
  We propose a Phase I-II dose escalation study for evaluating toxicity and efficacy with delayed outcomes by jointly modeling toxicity and efficacy as time-to-event outcomes. We apply our proposed design to a Phase I-II clinical trial of a novel targeted toxin for canine hemangiosarcoma.
  
  
  RESULTS
  Our simulation results show that our design identifies the optimal dose at a similar rate to dose finding that treats toxicity and efficacy as binary outcomes, but with substantial savings in study duration.
  
  
  CONCLUSIONS
  Our proposed design has acceptable operating characteristics and dramatically reduces the trial duration compared to a design that considers toxicity and efficacy as binary outcomes, but comes at the cost of enrolling additional subjects when all dose levels are unacceptable.
  
  
  CONCLUSIONS
  We developed a novel Phase I-II design that accounts for delayed outcomes by modeling toxicity and efficacy as time-to-event outcomes. Our design has similar operating characteristics to efficacy/toxicity trade-off designs that consider efficacy and toxicity as binary outcomes, but with a dramatically shorter study duration.
authors.affiliation: aDivision of Biostatistics, University of Minnesota, Minneapolis, MN, USA.
authors.forename: Joseph S
authors.initials: JS
authors.lastname: Koopmeiners
authors.forename: Jaime
authors.initials: J
authors.lastname: Modiano
mesh_terms: D000465:Algorithms; D000818:Animals; D001499:Bayes Theorem; D017321:Clinical Trials, Phase I as Topic / Q000379:methods*; D017322:Clinical Trials, Phase II as Topic / Q000379:methods*; D003198:Computer Simulation; D004285:Dogs; D004305:Dose-Response Relationship, Drug; D006801:Humans; D016015:Logistic Models; D020714:Maximum Tolerated Dose; D008962:Models, Theoretical; D012107:Research Design; D013997:Time Factors; D016896:Treatment Outcome